Thousands of financial academic research papers are published every year.Discover something which we can use it in the real trading world....
This article explains the Dispersion Trading Strategy coded in Python and has been authored by Jayesh Kurup as part of the EPAT™ coursework at QuantInsti®....
Pair Trading Strategy – Statistical Arbitrage on Cash Stocks coded in Python by Jonathan Narváez as part of the EPAT™ coursework at QuantInsti®....
A webinar on Classification of Quantitative Trading Strategies...
The effectiveness of the segregation is determined with the sample data that has the human and HFT algo that has the human and HFT algo order details....
Bitcoin is a first cryptocurrency that is decentralized, meaning one government or organization cannot control or regularize this, instead Bitcoin currency is managed by public....
This article covers the popular Quantiacs platform and the Python toolbox using which you can create, backtest and implement algorithmic trading strategies....
The conference featured expert workshops and talks on how one can overcome barriers to algorithmic trading, quantitative finance, and machine learning....
An exclusive conversation with a database research expert who decided to change his career to algorithmic research and EPAT™ helped him....
The article explains backtesting of the “52-Weeks High Effect in Stocks” trading strategy in R. The details of the strategy can be found on Quantpedia site....